Cloud Firestore 中的查詢可讓您在大型集合中尋找文件。若要深入了解整個集合的屬性,您可以聚合集合上的資料。
您可以在讀取時或寫入時聚合資料:
讀取時聚合在請求時計算結果。 Cloud Firestore 支援讀取時的
count()
、sum()
和average()
聚合查詢。讀取時聚合查詢比寫入時聚合更容易添加到您的應用程式中。有關聚合查詢的更多信息,請參閱使用聚合查詢匯總資料。寫入時聚合會在應用程式每次執行相關寫入操作時計算結果。寫入時聚合的實作需要更多工作,但出於以下原因之一,您可能會使用它們而不是讀取時聚合:
- 您想要監聽聚合結果以進行即時更新。
count()
、sum()
和average()
聚合查詢不支援即時更新。 - 您希望將聚合結果儲存在客戶端快取中。
count()
、sum()
和average()
聚合查詢不支援快取。 - 您正在為每個使用者聚合數以萬計的文件中的資料並考慮成本。文件數量越少,讀取時聚合的成本就越低。對於聚合中的大量文檔,寫入時聚合的成本可能會更低。
- 您想要監聽聚合結果以進行即時更新。
您可以使用客戶端事務或 Cloud Functions 來實現寫入時聚合。以下部分說明如何實現寫入時聚合。
解決方案:使用客戶端事務進行寫入時聚合
考慮一個可以幫助用戶找到很棒的餐廳的當地推薦應用程式。以下查詢檢索給定餐廳的所有評級:
網路
db.collection("restaurants") .doc("arinell-pizza") .collection("ratings") .get();
迅速
do { let snapshot = try await db.collection("restaurants") .document("arinell-pizza") .collection("ratings") .getDocuments() print(snapshot) } catch { print(error) }
Objective-C
FIRQuery *query = [[[self.db collectionWithPath:@"restaurants"] documentWithPath:@"arinell-pizza"] collectionWithPath:@"ratings"]; [query getDocumentsWithCompletion:^(FIRQuerySnapshot * _Nullable snapshot, NSError * _Nullable error) { // ... }];
Kotlin+KTX
db.collection("restaurants") .document("arinell-pizza") .collection("ratings") .get()
Java
db.collection("restaurants") .document("arinell-pizza") .collection("ratings") .get();
我們可以將此資訊儲存在餐廳文件本身上,而不是獲取所有評級然後計算聚合資訊:
網路
var arinellDoc = { name: 'Arinell Pizza', avgRating: 4.65, numRatings: 683 };
迅速
struct Restaurant { let name: String let avgRating: Float let numRatings: Int } let arinell = Restaurant(name: "Arinell Pizza", avgRating: 4.65, numRatings: 683)
Objective-C
@interface FIRRestaurant : NSObject @property (nonatomic, readonly) NSString *name; @property (nonatomic, readonly) float averageRating; @property (nonatomic, readonly) NSInteger ratingCount; - (instancetype)initWithName:(NSString *)name averageRating:(float)averageRating ratingCount:(NSInteger)ratingCount; @end @implementation FIRRestaurant - (instancetype)initWithName:(NSString *)name averageRating:(float)averageRating ratingCount:(NSInteger)ratingCount { self = [super init]; if (self != nil) { _name = name; _averageRating = averageRating; _ratingCount = ratingCount; } return self; } @end
Kotlin+KTX
data class Restaurant( // default values required for use with "toObject" internal var name: String = "", internal var avgRating: Double = 0.0, internal var numRatings: Int = 0, )
val arinell = Restaurant("Arinell Pizza", 4.65, 683)
Java
public class Restaurant { String name; double avgRating; int numRatings; public Restaurant(String name, double avgRating, int numRatings) { this.name = name; this.avgRating = avgRating; this.numRatings = numRatings; } }
Restaurant arinell = new Restaurant("Arinell Pizza", 4.65, 683);
為了保持這些聚合的一致性,每次將新評級新增至子集合時都必須更新它們。實現一致性的一種方法是在單一事務中執行新增和更新:
網路
function addRating(restaurantRef, rating) { // Create a reference for a new rating, for use inside the transaction var ratingRef = restaurantRef.collection('ratings').doc(); // In a transaction, add the new rating and update the aggregate totals return db.runTransaction((transaction) => { return transaction.get(restaurantRef).then((res) => { if (!res.exists) { throw "Document does not exist!"; } // Compute new number of ratings var newNumRatings = res.data().numRatings + 1; // Compute new average rating var oldRatingTotal = res.data().avgRating * res.data().numRatings; var newAvgRating = (oldRatingTotal + rating) / newNumRatings; // Commit to Firestore transaction.update(restaurantRef, { numRatings: newNumRatings, avgRating: newAvgRating }); transaction.set(ratingRef, { rating: rating }); }); }); }
迅速
func addRatingTransaction(restaurantRef: DocumentReference, rating: Float) async { let ratingRef: DocumentReference = restaurantRef.collection("ratings").document() do { let _ = try await db.runTransaction({ (transaction, errorPointer) -> Any? in do { let restaurantDocument = try transaction.getDocument(restaurantRef).data() guard var restaurantData = restaurantDocument else { return nil } // Compute new number of ratings let numRatings = restaurantData["numRatings"] as! Int let newNumRatings = numRatings + 1 // Compute new average rating let avgRating = restaurantData["avgRating"] as! Float let oldRatingTotal = avgRating * Float(numRatings) let newAvgRating = (oldRatingTotal + rating) / Float(newNumRatings) // Set new restaurant info restaurantData["numRatings"] = newNumRatings restaurantData["avgRating"] = newAvgRating // Commit to Firestore transaction.setData(restaurantData, forDocument: restaurantRef) transaction.setData(["rating": rating], forDocument: ratingRef) } catch { // Error getting restaurant data // ... } return nil }) } catch { // ... } }
Objective-C
- (void)addRatingTransactionWithRestaurantReference:(FIRDocumentReference *)restaurant rating:(float)rating { FIRDocumentReference *ratingReference = [[restaurant collectionWithPath:@"ratings"] documentWithAutoID]; [self.db runTransactionWithBlock:^id (FIRTransaction *transaction, NSError **errorPointer) { FIRDocumentSnapshot *restaurantSnapshot = [transaction getDocument:restaurant error:errorPointer]; if (restaurantSnapshot == nil) { return nil; } NSMutableDictionary *restaurantData = [restaurantSnapshot.data mutableCopy]; if (restaurantData == nil) { return nil; } // Compute new number of ratings NSInteger ratingCount = [restaurantData[@"numRatings"] integerValue]; NSInteger newRatingCount = ratingCount + 1; // Compute new average rating float averageRating = [restaurantData[@"avgRating"] floatValue]; float newAverageRating = (averageRating * ratingCount + rating) / newRatingCount; // Set new restaurant info restaurantData[@"numRatings"] = @(newRatingCount); restaurantData[@"avgRating"] = @(newAverageRating); // Commit to Firestore [transaction setData:restaurantData forDocument:restaurant]; [transaction setData:@{@"rating": @(rating)} forDocument:ratingReference]; return nil; } completion:^(id _Nullable result, NSError * _Nullable error) { // ... }]; }
Kotlin+KTX
private fun addRating(restaurantRef: DocumentReference, rating: Float): Task<Void> { // Create reference for new rating, for use inside the transaction val ratingRef = restaurantRef.collection("ratings").document() // In a transaction, add the new rating and update the aggregate totals return db.runTransaction { transaction -> val restaurant = transaction.get(restaurantRef).toObject<Restaurant>()!! // Compute new number of ratings val newNumRatings = restaurant.numRatings + 1 // Compute new average rating val oldRatingTotal = restaurant.avgRating * restaurant.numRatings val newAvgRating = (oldRatingTotal + rating) / newNumRatings // Set new restaurant info restaurant.numRatings = newNumRatings restaurant.avgRating = newAvgRating // Update restaurant transaction.set(restaurantRef, restaurant) // Update rating val data = hashMapOf<String, Any>( "rating" to rating, ) transaction.set(ratingRef, data, SetOptions.merge()) null } }
Java
private Task<Void> addRating(final DocumentReference restaurantRef, final float rating) { // Create reference for new rating, for use inside the transaction final DocumentReference ratingRef = restaurantRef.collection("ratings").document(); // In a transaction, add the new rating and update the aggregate totals return db.runTransaction(new Transaction.Function<Void>() { @Override public Void apply(@NonNull Transaction transaction) throws FirebaseFirestoreException { Restaurant restaurant = transaction.get(restaurantRef).toObject(Restaurant.class); // Compute new number of ratings int newNumRatings = restaurant.numRatings + 1; // Compute new average rating double oldRatingTotal = restaurant.avgRating * restaurant.numRatings; double newAvgRating = (oldRatingTotal + rating) / newNumRatings; // Set new restaurant info restaurant.numRatings = newNumRatings; restaurant.avgRating = newAvgRating; // Update restaurant transaction.set(restaurantRef, restaurant); // Update rating Map<String, Object> data = new HashMap<>(); data.put("rating", rating); transaction.set(ratingRef, data, SetOptions.merge()); return null; } }); }
使用事務可以使聚合資料與底層集合保持一致。若要詳細了解 Cloud Firestore 中的事務,請參閱事務和批次寫入。
限制
上面顯示的解決方案示範了使用 Cloud Firestore 用戶端庫聚合數據,但您應該注意以下限制:
- 安全性- 客戶端事務需要授予客戶端更新資料庫中聚合資料的權限。雖然您可以透過撰寫進階安全規則來降低此方法的風險,但這可能不適合所有情況。
- 離線支援- 當使用者的裝置離線時,客戶端交易將會失敗,這表示您需要在應用程式中處理這種情況,並在適當的時間重試。
- 效能- 如果您的事務包含多個讀取、寫入和更新操作,則可能需要向 Cloud Firestore 後端發出多個請求。在行動裝置上,這可能需要大量時間。
- 寫入速率- 此解決方案可能不適用於頻繁更新的聚合,因為 Cloud Firestore 文件每秒最多只能更新一次。此外,如果事務讀取在事務外部修改的文檔,它會重試有限次數,然後失敗。查看分散式計數器,了解需要更頻繁更新的聚合的相關解決方法。
解決方案:使用 Cloud Functions 進行寫入時聚合
如果客戶端交易不適合您的應用程序,您可以使用雲端函數在每次向餐廳添加新評級時更新聚合資訊:
Node.js
exports.aggregateRatings = functions.firestore .document('restaurants/{restId}/ratings/{ratingId}') .onWrite(async (change, context) => { // Get value of the newly added rating const ratingVal = change.after.data().rating; // Get a reference to the restaurant const restRef = db.collection('restaurants').doc(context.params.restId); // Update aggregations in a transaction await db.runTransaction(async (transaction) => { const restDoc = await transaction.get(restRef); // Compute new number of ratings const newNumRatings = restDoc.data().numRatings + 1; // Compute new average rating const oldRatingTotal = restDoc.data().avgRating * restDoc.data().numRatings; const newAvgRating = (oldRatingTotal + ratingVal) / newNumRatings; // Update restaurant info transaction.update(restRef, { avgRating: newAvgRating, numRatings: newNumRatings }); }); });
該解決方案將工作從客戶端卸載到託管功能,這意味著您的行動應用程式可以添加評級,而無需等待交易完成。在雲端函數中執行的程式碼不受安全規則的約束,這表示您不再需要向客戶端授予對聚合資料的寫入存取權限。
限制
使用雲端函數進行聚合可以避免客戶端事務的一些問題,但會帶來一組不同的限制:
- 成本- 添加的每個評級都會導致一次 Cloud Function 調用,這可能會增加您的成本。有關更多信息,請參閱 Cloud Functions定價頁面。
- 延遲- 透過將聚合工作卸載到雲端函數,您的應用程式將不會看到更新的數據,直到雲端函數完成執行並且客戶端已收到新數據的通知。根據雲端功能的速度,這可能比在本地執行事務需要更長的時間。
- 寫入速率- 此解決方案可能不適用於頻繁更新的聚合,因為 Cloud Firestore 文件每秒最多只能更新一次。此外,如果事務讀取在事務外部修改的文檔,它會重試有限次數,然後失敗。查看分散式計數器,了解需要更頻繁更新的聚合的相關解決方法。